In many industries, decisions that have future consequences generally attempt to account for an amount of uncertainty in the future consequence. For example, when manufacturers decide whether to start a project for the development, manufacture and sale of a good, those manufacturers try to account for future benefits associated with the good, such as future profits or revenues generated by the good, and/or units of the good produced. For example, the future revenues generated by a good can depend in large part on a number of factors, including an amount of uncertainty that can result in those future revenues actually being represented over a range of possible values.
Traditionally, manufacturers have not been capable of reliably quantifying a forecast of future revenues for projects when a significant amount of uncertainty exists. In this regard, techniques such as the price path formulation associated with Brownian motion and lattice techniques, have been developed to model uncertainty, sometimes referred to as a “cone of uncertainty,” with the path of future revenues modeled within the cone. Whereas such techniques adequately model uncertainty and future revenues, they have shortcomings in certain, but crucial, applications. For example, such techniques are typically unable to easily incorporate changes in uncertainty over time. Also, for example, such techniques are typically unable to easily account for contingent decisions that may occur during a given time period.
Both Brownian motion and lattice techniques typically operate by defining a constant amount of uncertainty and a constant amount of growth in revenues over a period of time, and do not account for contingencies such as internal and/or external activities or endeavors. It will be appreciated, however, that in many actual instances, uncertainty and/or growth rate can vary from time segment to time segment over a period of time. In addition, in many actual instances, uncertainty and/or growth rate can take into account internal and external activities or endeavors, which may or may not be conditional, such as the payout of a dividend, entry of a competitor into the market, change in governmental regulations, or agreement for revenue sharing. Thus, conventional techniques such as the Brownian motion and lattice techniques, do not provide adequate flexibility to thereby accurately model uncertainty for future revenues.